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public health. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in
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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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-efficient methods for acquiring tree-level data to support precision forestry. About the position You will work at the interface of advanced remote sensing and practical forest management. The research
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substantial experimental components that should be published in peer-reviewed international journals and at major conferences. The position will include supervision of PhD and MSc students, teaching and
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has about 250 employees of which 95 are PhD students. Many have been internationally recruited. The Department is part of the AlbaNova University Center, which apart from the Department of Physics
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of viruses, primarily using electron microscopy, complemented by other methods to understand structure and function. The project involves structural studies of diatom viruses with the aim of increasing
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of the sea, with a focus on questions related to marine protected areas About the position You will primarily work on developing and applying video-based methods for monitoring fish in protected areas and
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methods to simulate between functional chemically active surfaces and molecules/liquids. Central methodologies include: static DFT calculations; TBMD and AIMD; classical atomistic and coarse-grained
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primarily work on developing and applying video-based methods for monitoring fish in protected areas and increasing knowledge about ecosystem function. The work includes method development for AI-supported
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team of atmospheric modellers at the department. Qualification requirements Requirements: The applicant must have a PhD degree in atmospheric science or simular. Applicant must have work life experience